What is the purpose of sampling in population studies?
Estimate population characteristics
Population density, D, can be estimated using the formula: D= \frac{\text{Number of individuals \in sample}}{\text{Area of sample plot}} and is used to determine density
Steps to perform random sampling
1️⃣ Identify the Population
2️⃣ Assign Numbers
3️⃣ Select Numbers
4️⃣ Collect Sample
Random sampling is suitable for populations with uneven distribution.
False
What is stratified sampling used for?
Ensure representative samples
Match the sampling technique with its description:
Random Sampling ↔️ Equal chance for all
Systematic Sampling ↔️ Regular intervals
Stratified Sampling ↔️ Subgroups based on characteristics
To ensure representativeness, the sample size must be large enough to provide accurate estimates
Stratified sampling reduces sampling error in heterogeneous populations.
What is stratified sampling?
Dividing population into subgroups
One advantage of stratified sampling is that it ensures each stratum contributes proportionally
Stratified sampling reduces sampling error compared to random sampling in heterogeneous populations.
In the proportional allocation formula, what does Ni represent?
Size of stratum i
Steps involved in systematic sampling
1️⃣ Define the population
2️⃣ Calculate the sampling interval
3️⃣ Choose a random start
4️⃣ Select every Kth individual
What is a disadvantage of systematic sampling?
Potential bias
Sampling allows for efficient estimation of population characteristics like density, distribution, and demographics
A well-designed sample can accurately represent the entire population.
What is the formula for estimating population density?
D= \frac{\text{Number of individuals \in sample}}{\text{Area of sample plot}}
Match the sampling technique with its description:
Random sampling ↔️ Every individual has equal chance
Systematic sampling ↔️ Individuals selected at regular intervals
Stratified sampling ↔️ Population divided into subgroups
What is a weakness of random sampling?
May not cover population
Systematic sampling is suitable for large, consistent areas.
What is the primary goal of random sampling?
Ensure unbiased sample
The first step in random sampling is to identify the population
Steps involved in random sampling
1️⃣ Identify the population
2️⃣ Assign unique numbers
3️⃣ Select numbers randomly
4️⃣ Collect the sample
A large sample size is necessary to ensure representativeness in random sampling.
Stratified sampling ensures each stratum contributes proportionally
In the proportional allocation formula, what does n represent?
Total sample size
Systematic sampling can introduce bias if the sampling interval aligns with population patterns.
How does systematic sampling compare to random sampling in terms of structure and randomness?
More structured, less random
The main sampling techniques used in population studies include Random Sampling, Systematic Sampling, and Stratified
Random sampling ensures unbiased selection but may not cover the entire population effectively.
What type of population is random sampling best suited for?
Uniformly distributed
What is a weakness of systematic sampling?
Can introduce bias
Stratified sampling requires detailed knowledge of subgroups to ensure representative samples.
The choice of sampling technique depends on the population's distribution and characteristics
What is a practical example of random sampling in ecological investigations?
Estimating dandelions in a field
The sampling interval in systematic sampling is calculated as K=nN, where N is the population size
Why is stratified sampling used in heterogeneous environments?
Ensures representation from each stratum
Systematic sampling is ideal for linear surveys, such as along a transect.
Match the sampling technique with its ecological application:
Random Sampling ↔️ Estimating uniformly distributed species
Systematic Sampling ↔️ Surveying vegetation along a transect
Stratified Sampling ↔️ Studying diverse ecosystems